Background

Malaria incidence appears to be decreasing worldwide as a result of mass interventions and other factors [1, 2]. The decreasing pattern of incidence is encouraging and the international community has recently been challenged to re-evaluate the prospects for malaria eradication [3]. Falciparum malaria is the most deadly among the four main types of human malaria. The number of clinical events caused by Plasmodium falciparum was estimated to be 515 million worldwide in 2002 [4]. Falciparum malaria transmission is a global problem requiring a global intervention strategy with regional targets. While most falciparum attacks are concentrated in the African region (70%), the densely populated Southeast Asia region contributed 25% of the clinical attacks in 2002 [4]. The Southeast Asia region has also been the focus for the origin of drug-resistant malaria, which may have contributed to the rising mortality from malaria in the African region since 1990 [5]. The epidemic situation in China is largely affected by that in the nearby Southeast Asian countries [6].

Although great success has been achieved since the launch of National Malaria Control Programme in 1955, malaria remains a serious public health problem in China [7–9]. Falciparum malaria, the most deadly among the four main types of human malaria, accounted for 14.9% of all blood-test confirmed malaria cases in 1998 [10]. Falciparum malaria had been endemic in fifteen provinces of China in the early 1950s. Integrated measures for malaria control, involving the vector as well as malaria infections, were effective in eliminating falciparum malaria in central China [12, 14], was then mapped at county level in the two endemic provinces, Yunnan and Hainan. PfAPI was classified into three categories: no autochthonous falciparum cases reported, < 0.1 autochthonous falciparum cases per 1,000 people pa, and ≥ 0.1 autochthonous falciparum cases per 1,000 people pa. These three categories were defined as stable, non-stable, or no risk of falciparum malaria transmission [15]. The number of confirmed cases and Pf API, respectively, were mapped by matching them to their corresponding province- and county-level administrative units in a geographic information system (ArcGIS 9.0, ESRI, Redlands, CA).

Time-series analysis was conducted to investigate the relationship between the falciparum malaria in the endemic provinces and the imported malaria in non-endemic provinces of China. An auto-regressive integrated moving average (ARIMA) model was fit first to the predictor variable. The model was then applied to the dependent variable before the two series were cross-correlated to determine whether an association exists. ARIMA was designed to deal with highly seasonal data. Modeling with ARIMA involves the estimation of a series of parameters to account for the inherent dynamics in the time series, including the trends and autoregressive and moving average processes. The general model introduced by Box and Jenkin [16] includes autoregressive and moving average parameters, and explicitly includes differencing in the formulation of the model. An ARIMA (p, d, q) model comprises three types of parameters: the autoregressive parameters (p), number of differencing passes (d), and moving average parameters (q). The multiplicative seasonal ARIMA (p, d, q)(P, D, Q) s model is an extension of the ARIMA method to time series in which a pattern repeats seasonally over time. Analogous to the simple ARIMA parameters, the seasonal parameters are: seasonal autoregressive (P), seasonal differencing (D), and seasonal moving average parameters (Q). The length of the seasonal period is represented by s. The input series of incidence rates in the two malaria endemic provinces, at lags of 0–2 months, were fitted in the ARIMA model of the incidence rate in the non-endemic provinces of China. The selection of ARIMA processes was conducted using Akaike's information criterion (AIC), which measures how well the model fits the series.

Results

Figure 1 shows the province-level distribution of falciparum malaria cases in China during 2004–05. Falciparum malaria cases were reported all over China except in four provinces in the west (** arrangements may lead to different patterns of exposure to mosquitoes for men and women [22]. Compared with women in some societies, men have a greater occupational risk if they work in mines, fields or forests at peak biting times, or migrate to areas of high endemicity for work [23]. For example, the exophilic Anopheles dirus is the principal vector for falciparum malaria in the hilly-forested endemic area of Hainan and SE Asia [24]; more working hours outdoors may have contributed to the higher malaria risk among men. The sex ratio of falciparum malaria numbers in the children of 0–15 years was not as skewed as that in adults; the sex ratio of incidence rate was unknown because of the lack of age-specific population data.

Imported falciparum malaria has spread to more provinces in the non-endemic area in China. Reported in only two non-endemic provinces in 1984, imported falciparum malaria was found in 16 provinces in 1998 [10]. As revealed in the present paper, imported Pf malaria cases were reported in 26 provinces of China during 2004–05. In line with the spatial expansion, there was also a temporal increase of the number of imported malaria cases in China. The fraction of imported cases increased from 5% in 1992 to 8% in 2005. Increased population movement, domestic and international, may have contributed to the spread of imported falciparum malaria in China [25, 26]. The origin of infection was traced to the endemic areas of Yunnan and Hainan Provinces of China, SE Asia and Africa [27]. Identifying and understanding the influence of these population movements can improve the malaria intervention measures [28].

Time-series analysis revealed that the imported falciparum malaria in China was influenced mainly by the endemic malaria in Yunnan Province, which was in turn affected by the bordering SE Asia countries: Myanmar, Laos and Vietnam. Time-series analysis has been used extensively in the study of infectious diseases and ARIMA models are useful tools to analyse time-series data containing seasonal trends [29–31]. In the current study, falciparum malaria in Yunnan was positively correlated with the imported malaria of concurrent months in the non-endemic provinces of China. Imported malaria also occur between the endemic areas of Yunnan, China and SE Asia due to the frequent cross-border population movement. Imported cases accounted for a large fraction of adult infections in Yunnan: 22% in men and 13% in women. In a survey among mobile population in the border area of Yunnan, P. falciparum parasite rates (Pf PR) was 3.1% for the SE Asian entering Yunnan and 0.7% for the local people returning from SE Asia visits [32]. Intervention measures tailored to these mobile populations are warranted in the future malaria control programmes.

The primary limitation of the current study is that all analyses were based solely on the national surveillance data, which is compromized by underreporting of malaria. As high as 90% of malaria cases may go unreported in China [33]. The skewed gender distribution of falciparum malaria in the endemic areas could be partially explained by the gender-differentiated underreporting. Moreover, the spatial and demographic analyses were based on a short period of time, 2004–2005. Despite these limitations, this study provides valuable information on the geographic distribution, demographic patterns and time trends of falciparum malaria in China.

Conclusion

The endemic area of falciparum malaria in China has remained restricted to two provinces, Yunnan and Hainan. Stable falciparum malaria transmission occurs in the bordering region of Yunnan and the hilly-forested south of Hainan. The age and gender distribution in the endemic area is characterized by the predominance of adult men cases. Imported falciparum malaria in the non-endemic area of China, affected mainly by the malaria transmission in Yunnan, has increased both spatially and temporarily. Specific intervention measures targeted at the mobile population groups are warranted.